1 Overview

Forecasts of climate impacts on marine populations have often struggled to pass peer-review. Typically, those forecasts are also highly uncertain. These forecasting challenges have proven an impediment to the adoption of fishery management practices that are considerate of climate change.

To alleviate the need for a defensible forecast, the Climate Test rephrases the problem, focusing on the relative performance of management options given increasingly extreme climate scenarios. This is analogous to testing pilots in a simulator. It is possible to simulation test and then rate pilots according to their ability to fly under increasingly challenging weather conditions. This pilot rating process is unrelated to a particular weather forecast.

The aim of Climate Test is to provide strategic information to fishery managers about the relative climate robustness of various candidate management options. For a set of candidate management procedures that are otherwise comparable, managers have the option of adopting a procedure that has been show to withstand more extreme climate tests.

2 Project Details

Title: ‘Create and demonstrate a practical, science-based framework that enables fisheries managers to evaluate and adopt climate-resilient management procedures’

Term Sept 2025 - Nov 2027
Funded by Paul M. Angell Family Foundation, Oceankind, The Pew Charitable Trusts
Coordinated by The Ocean Foundation (TOF)
Initiative www.HarvestStrategies.org
Project Partners Blue Matter Science Ltd., University of Cape Town (UCT)
TOF Project Leader Rebecca Scott
Blue Matter Team Tom Carruthers, Adrian Hordyk, Quang Huynh
UCT Collaborators Carryn de Moor, Kelly Ortega-Cisneros

3 Introduction

3.1 Hypothesized Climate Impacts on Exploited Marine Populations

Changing climatic conditions have the potential to substantially alter the abundance, productivity and species composition of pelagic marine ecosystems (Beaugrand and Kirby 2023, Bell et al. 2011). Due to increasing anthropogenic greenhouse gas emissions, climate processes affecting marine ecosystems are forecasted to intensify (Hoehy-Guldberg et al. 2018; Kwiatkowski et al., 2020).

Climate processes (e.g., thermal regime, concentration of greenhouse gasses) are linked to oceanographic conditions (e.g., ocean temperature, ocean mixing, stratification, pH & salinity)(Figure 1, Table 1). A large number of mechanisms have been proposed for how individual fish stocks may be impacted by those changing oceanographic conditions (Table 2). The mechanistic linkages are numerous and can related to changing ecological processes (e.g., primary productivity, community dynamics) and the location and amount of suitable habitat. The large number of mechanisms ultimately impact a relatively concise list of individual stock dynamics relating to species distribution, survival of various life stages, condition factor, fecundity and somatic growth (Walther et al., 2002; Doney et al., 2012; Free et al., 2019).

Figure 1. A simplified diagram of linkages among climate processes, oceanographic conditions and individual species dynamics. The size of each box is intended to represent the relative number of processes / mechanisms that have been proposed in the literature, highlighting the relatively small number of hypothesized impacts on individual species.


In their review of impacts on large pelagic fish in the Northwest Atlantic, Dell’Apa et al. (2023) provide a useful example of changes in ocean conditions that may impact stock dynamics:

“… the Northwest Atlantic Ocean has been characterized by several climate-driven changes in regional environmental conditions over recent decades, including warmer sea surface temperature (SST) (Karnauskas et al., 2013; Loder and Wang, 2015) and bottom water temperature (Brickman et al., 2018), increased summertime stratification of shelf waters (Li et al., 2015), changes in dissolved oxygen concentration (DO) levels (Stendardo and Gruber, 2012) and acidification (Cai et al., 2011), and altered oceanographic processes (Karnauskas et al., 2015)”.

Establishing climate-ready management is a key priority for many regional fishery management organizations in light of persistent declines in various species (Pacoureau et al. 2021) and concern that fishing may increase the sensitivity of marine populations to climate change (Hsieh et al. 2008).

Evaluating the climate-readiness of current and alternative management options requires models that can predict fishery and population dynamics. Unfortunately, forecasting the impacts of climate changes on managed pelagic species is highly uncertain. In theory, it is possible for example, to combine models of emissions (e.g., Algieri et al. 2023, Wang et al. 2017), earth systems (Kawamiya et al. 2020), ecosystems (e.g., Beaugrand and Kirby 2018, Lehodey et al. 2010; 2011), behaviour (e.g., Bushnell and Brill 1991, Cayré and Marsac 1993) and physiology (e.g., Gooding et al. 1981, Graham et al. 1989, Essington 2003, Checkley et al. 2009). In doing so, forecasting combines a complex series of linked projections that include greenhouse gas emissions (least uncertain), response of climate processes (uncertain), linkages with oceanographic conditions (more uncertain) and the expected impact of those on pelagic communities and individual species (most uncertain). It follows that any climate change scenario for establishing climate-ready management advice for a given fish stock is firmly hypothetical, and the relative credibility of scenarios should be considered highly uncertain.

Table 1. Proposed linkages between climatological processes and oceanographic properties impacting fish habitat.


This large uncertainty over climate impact scenarios poses a problem for the provision of ‘climate ready’ fishery management advice using the contemporary stock assessment and management strategy evaluation (MSE) frameworks. That is because those frameworks rely on the specification of models that represent climate impacts and the assigned credibility of those models could strongly affect the advice provided. For example, there may be small or large future changes in natural survival. Advice arising from scenarios with low survival changes would likely lead to the provision of strongly differing advice from scenarios with high natural survival, yet the relative credibility of those scenarios is not easily evaluated.

Although there are very few quantitative forecasts of climate impacts on fisheries, qualitatively the way in which climate can impact individual populations has been hypothesized in numerous papers (Table 2). The most frequently hypothesized population changes relate to recruitment (carrying capacity, spawning habitat, larval survival), adult survival (natural mortality rate), somatic growth, spatial distribution (range contraction, catchability) age-at-maturity and condition factor (weight-at-length, fecundity). Additionally, the problematic direction of change in those variables is established: lower recruitment strength, decreased survival, lower somatic growth rate, reduced spatial distribution, older age-at-maturity and poorer condition factor. The incredibly large body of theoretical work is distilled into a very small set of single stock climate impacts.

Table 2. Mechanistic linkages between oceanographic properties impacting fish habitat and the dynamics of individual stocks (or operating models).


3.2 Climate Test: Metrics of Climate Robustness

Rather than leaving the investigation of climate resilience stalled in the (perhaps indefinite) wait for scientifically defensible forecasts of climate impacts, the Climate Test presents an alternative approach. The solution proposed here is to shift the focus from forecast-based tests of climate robustness in favor of performance metrics of climate robustness. This is analogous to testing pilots in a simulator under an increasingly difficult set of weather conditions. We do not need a weather forecast to know those pilots that are better at flying in more extreme weather conditions. The Climate Test increases the degree of climate impact to identify those management options that most robust.

3.3 Management Strategy Evaluation

The Climate Test is proposed as an extension to management strategy evaluation (MSE), a process that has two essential components for climate test already specified: (1) models of system dynamics (operating models) and (2) candidate management options (management procedures, harvest strategies). The intention of Climate Test is to be a straightforward addition to any MSE process established in the openMSE framework (an extension R package) allowing for climate-considerate management advice in more than 20 current MSEs.

4 Methods

4.1 Robustness Threshold

The climate test compares when management options ‘break’ due to climate impacts and hence requires a definition of that break point, a ‘Robustness threshold’. The Robustness threshold has three parts: (1) an unacceptable level of impact, (2) a quantity that is impacted and (3) a time horizon.

In Figure 2 a climate test is presented for two management procedures for Atlantic Blue Shark (Carruthers XXX). In this case the robustness threshold is a 30% decline in spawning stock biomass (SSB) over a 30 year time horizon. The two management procedures were climate tested for declines in somatic growth (K). The top row shows how future spawning biomass is impacted by increasingly large impacts on somatic growth (phrased as annual percentage declines in K).

The first management procedure (top row) crosses the robustness threshold after 30 years given a decline in growth of 8%. The second management procedure (bottom row) is much more robust and it takes an 18% decline in somatic growth before projected biomass crosses the performance threshold.

Figure 2. An exploratory climate test of decreasing somatic growth for two management procedures applied to Atlantic blueshark operating model (Carruthers 2024b)


4.2 Exploratory Tests

For any case study it is possible to create a set of marginal (one parameter at a time) climate tests to rate the climate robustness of candidate management procedures. Despite a large number of proposed mechanisms, there are only six frequently cited impacts on individual stocks and the problematic direction for management is known (Table 3)

Table 3. Six exploratory climate tests identified in Carruthers 2024a

Parameter Code Description
Somatic Growth K Declines in somatic growth may lead to fewer mature fecund individuals in the population, a higher fraction of fish caught per catch weight, and a lower rate of sustainable harvest
Recruitment Strength R Declines in recruitment strength require fewer catches to maintain stock sizes
Natural Mortality M Declining natural survival (increasing M) reduces the number of cohorts in the population, and reduces the likelihood of reaching maturity
Condition Factor C Declining condition factor reduces spawning biomass, increases the number of fish caught per catch weight and reduces the rate of sustainable harvest
Spatial distribution Q Spatial range contration towards fishing can increase catchability (fishing efficiency) leading to higher catch per effort
Carrying Capacity S Declines in carrying capacity reduce stock-wide productivity reducing sustainable catch levels


These marginal climate tests can be used to rate MPs according to the level of climate impact before the robustness threshold is crossed. Table 4 shows four marginal tests for six example management procedures for blue shark (Carruthers 2024b).

Table 4. An example of exploratory climate tests of decreasing: natural survival (M), mean recruitment strength (R), condition factor (C) and somatic growth (K) for six generic management procedures applied to a Atlantic blueshark operating model (Carruthers 2024b). Numbers represent the percentage change in each exploratory test before the robustness threshold was crossed. Higher numbers indicate higher impacts and hence a more climate robust management procedure.


4.3 Conceptual Test

Conceptual tests differ from exploratory tests in that they use a theoretical model to predict the combined impacts of climate at the same time. For example, rather than separately rating MP robustness given increasing the natural mortality rate (M) and reductions in somatic growth (K), the conceptual test makes a paired projection of these parameters, linking them by a theoretical ecosystem model.

Figure 3. Three individual future projections of natural mortality rate (M, increasing) and somatic growth rate (K, decreasing). The two parameters are negatively correlated, and constrained theoretically by the equations of the ecosystem model. The three lines represent three individual projections at low, medium and high climate impacts (green, orange, red). Changes are phrased as a mulitple of current levels (e.g. they start at 1 in 2024).


Figure 4. As Figure 3 but including the projected values of 10 simulations combined.

In combined tests, all parameters change with increasing climate impact so results are easily presented graphically along a continuum of climate impact (Figure 5).

Figure 5. The Combined Climate test. The robustness of MPs can be rated over a finer resolution of climate impacts than presented in Figure 4 (which only had three). In this case MPs are rated according to whether they could remain above 80% of current spawning stock biomass (dashed horizontal line, with increasing ocean warming scenario). When they cross this robustness threshold they are scored according to the degrees of warming when this occurred. In this case MP1 is the most robust crossing the robustness threshold after a warming of 0.9 degrees.


4.4 Tailored Test

Tailored tests are identical to conceptual tests but they are based on ecosystem models specified and calibrated for the particular case study stock. For example, the conceptual test might apply model-based projections for a lower trophic level pelagic fish stock. The tailored test would be an ecosystem model for the Inside Strait of Georgia with projections for Pacific herring based on the herring component of that model.

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8 Acknowledgements


ClimateTest is funded by:

The Paul M. Angell Family Foundation Oceankind The Pew Charitable Trusts

and

The Ocean Foundation in partnership with www.HarvestStrategies.org